- Code MATH3511
- Unit Value 6 units
This course presents the basic elements of scientific computing, in particular the methods for solving or approximating the solution of calculus and linear algebra problems associated with real world problems. Using a non-trivial model problem such as the heat equation, and sophisticated scientific computing and visualisation environments, students are introduced to the basic computational concepts of stability, accuracy and efficiency, as new numerical methods and techniques are introduced to solve progressively more challenging problems.
Honours Pathway Option (HPO):
To do this option, students must have completed MATH2405 or STAT2001 or a mark of 60% or more in MATH2305 or MATH1116. The HPO expands on the theoretical aspects of the underlying algorithms, and uses alternative assessment to assess these theoretical aspects.
Upon successful completion, students will have the knowledge and skills to:
On satisfying the requirements of this course, students will have the knowledge and skills to:
1. Use high-level programming language such as Python with proficiency and confidence
2. Use appropriate tools to verify the output and reliability of code/data
3. Use computing and visualisation software appropriately in scientific or engineering problems
Assessment will be based on:
- 10 workshop responses demonstrating capacity to use relevant software (30%; LO 1, 2, 3)
- 5 written assignments demonstrating a problem-based understanding of algorithms (30%; LO 1, 2, 3)
- Final examination (40%; LO, 1, 2, 3)
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WorkloadThree lectures per week and regular workshops/computer labs.
Requisite and Incompatibility
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- Student Contribution Band:
- Unit value:
- 6 units
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.